Abstract

The paper aims at synthesis of an adaptive controller of the distillate output flow rate of a binary distillation column. The disturbance of the process is the change of concentration of the inlet compound. The Adaptive Critic Design (ACD) approach was applied to predict on time the future effect of disturbance and to adapt the distillate output flow rate in order to prevent deviations from the desired distillate concentration. The key element of ACD-The critic-is a fast trainable recurrent neural network named Echo state network (ESN). The simulation investigations demonstrated that the proposed adaptive control scheme outperforms a classical non-adaptive controller with respect to the settling time and the reaction delay.

Original language

English

Title of host publication

Proceedings of the 2017 21st International Conference on Process Control, PC 2017

title = "Adaptive control of distillation column using adaptive critic design",

abstract = "The paper aims at synthesis of an adaptive controller of the distillate output flow rate of a binary distillation column. The disturbance of the process is the change of concentration of the inlet compound. The Adaptive Critic Design (ACD) approach was applied to predict on time the future effect of disturbance and to adapt the distillate output flow rate in order to prevent deviations from the desired distillate concentration. The key element of ACD-The critic-is a fast trainable recurrent neural network named Echo state network (ESN). The simulation investigations demonstrated that the proposed adaptive control scheme outperforms a classical non-adaptive controller with respect to the settling time and the reaction delay.",

N2 - The paper aims at synthesis of an adaptive controller of the distillate output flow rate of a binary distillation column. The disturbance of the process is the change of concentration of the inlet compound. The Adaptive Critic Design (ACD) approach was applied to predict on time the future effect of disturbance and to adapt the distillate output flow rate in order to prevent deviations from the desired distillate concentration. The key element of ACD-The critic-is a fast trainable recurrent neural network named Echo state network (ESN). The simulation investigations demonstrated that the proposed adaptive control scheme outperforms a classical non-adaptive controller with respect to the settling time and the reaction delay.

AB - The paper aims at synthesis of an adaptive controller of the distillate output flow rate of a binary distillation column. The disturbance of the process is the change of concentration of the inlet compound. The Adaptive Critic Design (ACD) approach was applied to predict on time the future effect of disturbance and to adapt the distillate output flow rate in order to prevent deviations from the desired distillate concentration. The key element of ACD-The critic-is a fast trainable recurrent neural network named Echo state network (ESN). The simulation investigations demonstrated that the proposed adaptive control scheme outperforms a classical non-adaptive controller with respect to the settling time and the reaction delay.